相关论文: A library of ab initio Raman spectra for automated…
Two-dimensional (2D) materials have attracted extensive attention due to their unique characteristics and application potentials. Raman spectroscopy, as a rapid and non-destructive probe, exhibits distinct features and holds notable…
Lattice structure and symmetry of two-dimensional (2D) layered materials are of key importance to their fundamental mechanical, thermal, electronic and optical properties. Raman spectroscopy, as a convenient and nondestructive tool, however…
Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its atomic structure and chemical composition. Interpretation of…
Raman spectroscopy is a widely used, powerful, and nondestructive tool for studying the vibrational properties of bulk and low-dimensional materials. Raman spectra can be simulated using first-principles methods, but due to the high…
We introduce a machine learning prediction workflow to study the impact of defects on the Raman response of 2D materials. By combining the use of machine-learned interatomic potentials, the Raman-active $\Gamma$-weighted density of states…
Raman spectroscopy is an advantageous method for studying the local structure of materials, but the interpretation of measured spectra is complicated by the presence of oblique phonons in polycrystals of polar materials. Whilst group theory…
Raman spectroscopy is widely used to assess the quality of 2D materials thin films. This report focuses on $\rm{PtSe_2}$, a noble transition metal dichalcogenide which has the remarkable property to transit from a semi-conductor to a…
Two-dimensional materials are a class of atomically thin materials with assorted electronic and quantum properties. Accurate identification of layer thickness, especially for a single monolayer, is crucial for their characterization. This…
The C2DB is a highly curated open database organizing a wealth of computed properties for more than 4000 atomically thin two-dimensional (2D) materials. Here we report on new materials and properties that were added to the database since…
Raman spectroscopy is a powerful experimental technique for characterizing molecules and materials that is used in many laboratories. First-principles theoretical calculations of Raman spectra are important because they elucidate the…
Two-dimensional (2D) layered materials have been extensively studied owing to their fascinating and technologically relevant properties. Their functionalities can be often tailored by the interlayer stacking pattern. Low-frequency (LF)…
Modern materials science requires efficient processing and characterization techniques for low dimensional systems. Raman spectroscopy is an important non-destructive tool, which provides enormous information on these materials. This…
This work presents an automated three-point bending apparatus that can be used to study strain engineering and straintronics in two-dimensional materials. We benchmark the system by reporting reproducible strain tuned micro-reflectance,…
Since double resonance Raman (DRR) spectra are laser-energy dependent, the first-principles calculations of DRR for two-dimensional materials are challenging. Here, the DRR spectrum of monolayer MoTe$_2$ is calculated by home-made program,…
We introduce a scheme based on machine learning and deep neural networks to model the environmental dependence of the electronic polarizability in insulating materials. Application to liquid water shows that training the network with a…
Recently, the combination of robust one-dimensional convolutional neural networks (1-D CNNs) and Raman spectroscopy has shown great promise in rapid identification of unknown substances with good accuracy. Using this technique, researchers…
We present an \textit{ab initio} study based on density-functional theory of first- and second-order Raman spectra of graphene-based materials with different stacking arrangements and numbers of layers. Going from monolayer and bilayer…
Raman spectroscopy is an important characterization tool with diverse applications in many areas of research. We propose a machine learning method for predicting polarizabilities with the goal of providing Raman spectra from molecular…
Raman spectroscopy is an important tool in the study of vibrational properties and composition of molecules, peptides and even proteins. Raman spectra can be simulated based on the change of the electronic polarizability with vibrations,…
The most widely used method for obtaining high-quality two-dimensional materials is through mechanical exfoliation of bulk crystals. Manual identification of suitable flakes from the resulting random distribution of crystal thicknesses and…